---
title: "Tableone_Dryad"
output: html_document
---
```{r}
library(tableone)
```
```{r}
setwd("Z:/Kleer/Project Paper/Masterfiles/4. Testfiles/")
#setwd("/Volumes/KLIM$/Kleer/Project Paper/Masterfiles/4. Testfiles")
#setwd("/Volumes/KLIM$/Kleer/Project Paper/Submission/DRYAD")
```
```{r}
#read in data
data <- read.csv2("MASTERFILE_kleer_20210305.csv")
```
```{r}
data$Group <- factor(data$Group, levels = c("NHS", "SLE"))
#SLE <- systemic lupus erythematosus group
#NHS <- normal human serum (actualy has been plasma)
```
```{r}
wilcox.test(Age ~ Group, data=data)
# SLE and Control Group are not age matched
```
```{r}
#create data.frame SLEsubset for demographic and clinical characteristics of SLE patients
SLEsubset <- data[1:378, 1:256]
```
```{r}
#create data.frame NHSsubset for Demographic and clinical characteristics of healthy blood donors (control group)
NHSsubset <- data[379:478, 1:256]
```
```{r}
#create continuous and categorical variables for summary statistics
#Enthnical Background
SLEsubset$ENBG <- factor(SLEsubset$ENBG, levels = c(1,2,3,4,5), labels = c("Caucasian", "Asian", "African", "native American", "other"))
#create variable 1=active Disease, 0= inactive Disease
SLEsubset$PGA <- factor(SLEsubset$PGA,levels = c("inactive","moderat", "active", "very active"),labels = c(1,2,3,4))
SLEsubset$PGA <- as.numeric(SLEsubset$PGA)
SLEsubset$activity <- ifelse(SLEsubset$SELENA>=6 & SLEsubset$PGA >=2, yes=1,no=0)
SLEsubset$activity <- factor(SLEsubset$activity, levels = c(0,1),
labels=c("inactive", "active"))
#Fever
SLEsubset$FEV <- factor(SLEsubset$FEV, levels = c(0,1), labels = c("no", "yes"))
#Arthritis
SLEsubset$ARI <- factor(SLEsubset$ARI, levels = c(0,1), labels = c("no", "yes"))
#skin involvement
SLEsubset$skin_involvement <- ifelse(SLEsubset$MAL == 1 | #Malar rash
SLEsubset$APH == 1| #Mucosal ulcers
SLEsubset$ALO == 1, yes = 1, no= 0) #Alopecia
SLEsubset$skin_involvement <- factor(SLEsubset$skin_involvement, levels = c(0,1), labels = c("no", "yes"))
#Vasculitis
SLEsubset$EVA <- factor(SLEsubset$EVA, levels = c(0,1), labels = c("no", "yes"))
#Pericarditis or Pleuritis
SLEsubset$PLEPER <- ifelse(SLEsubset$PER ==1 |
SLEsubset$PLE == 1, yes = 1, no= 0)
SLEsubset$PLEPER <- factor(SLEsubset$PLEPER, levels = c(0,1), labels = c("no", "yes"))
#CNS-Involvement
SLEsubset$CNSinvolvement <- ifelse(SLEsubset$PSY ==1 | #Psychosis
SLEsubset$SEI ==1 | #Seizures
SLEsubset$OBD ==1, yes = 1, no=0) #organic Brain Syndrome,
SLEsubset$CNSinvolvement <- factor(SLEsubset$CNSinvolvement, levels = c(0,1), labels = c("no", "yes"))
#Leukopenia
SLEsubset$LEU <- factor(SLEsubset$LEU, levels = c(0,1), labels = c("no", "yes"))
#Thrombocytopenia
SLEsubset$PLA <- factor(SLEsubset$PLA, levels = c(0,1), labels = c("no", "yes"))
#Proteinuria
SLEsubset$PRO <- factor(SLEsubset$PRO, levels = c(0,1), labels = c("no", "yes"))
#Hematuria
SLEsubset$HUM<- factor(SLEsubset$HUM, levels = c(0,1), labels = c("no", "yes"))
#low Complement
SLEsubset$TCO <- factor(SLEsubset$TCO, levels = c(0,1), labels = c("no", "yes"))
#anti-ds-DNA
SLEsubset$DNA<- factor(SLEsubset$DNA, levels = c(0,1), labels = c("no", "yes"))
#Amemia
SLEsubset$Anemia <- ifelse(SLEsubset$sex == "Female" & SLEsubset$HGB < 120, yes= 1,
no = ifelse(SLEsubset$sex == "Male" & SLEsubset$HGB < 130,
yes=1, no=0))
SLEsubset$Anemia <- factor(SLEsubset$Anemia, levels = c(0,1), labels = c("no", "yes"))
# elevated erythrocyte sedimentation rate
SLEsubset$ESRelevated <-
ifelse(SLEsubset$sex == "Female" & SLEsubset$Age <= 50 & SLEsubset$ESR > 20, yes=1,
no = ifelse(SLEsubset== "Female" & SLEsubset$Age > 50 & SLEsubset$ESR > 30, yes=1,
no = ifelse(SLEsubset$sex == "Male" & SLEsubset$Age <=50 &
SLEsubset$ESR > 15, yes=1, no = ifelse(SLEsubset$sex == "Male" & SLEsubset$Age > 50 & SLEsubset$ESR > 20, yes= 1, no= 0 ))))
SLEsubset$ESRelevated <- factor(SLEsubset$ESRelevated, levels = c(0,1), labels = c("no", "yes"))
#Antiphospholipid-Antibodies
SLEsubset$APA[SLEsubset$APA == "Present"] <- 1
SLEsubset$APA[SLEsubset$APA == "Absent"] <- 0
SLEsubset$APA[SLEsubset$APA == 99] <- NA
SLEsubset$APA <- as.numeric(SLEsubset$APA)
SLEsubset$APA <- factor(SLEsubset$APA, levels = c(0,1), labels = c("no", "yes"))
```
```{r}
# create variable list for Table one (SLE patients)
variablesSLE <- c("sex", "NACRC", "ENBG", "Age", "DDDXBE", "activity", "FEV", "ARI", "skin_involvement", "EVA","PLEPER", "CNSinvolvement", "LEU","PLA","PRO","HUM","TCO","DNA", "Anemia", "ESRelevated", "APA")
#Create Table one
tableoneSLE <- CreateTableOne(data=SLEsubset,
vars= variablesSLE)
#Summary of Table one
summary(tableoneSLE)
```
```{r}
# create variables for Table one from (Control Group)
variablesNHS <- c("sex", "Age")
#Create Table one
tableoneNHS <- CreateTableOne(data=NHSsubset,
vars= variablesNHS)
#Summary of Table one
summary(tableoneNHS)
```